Volume dimensioning system calibration systems and methods

ABSTRACT

Various corporate, industry, and regulatory guidelines, best practices and standards are used in establishing acceptable levels of accuracy for volume dimensioning systems used in commerce. A volume dimensioning system can determine at least one distortion value that is indicative of an amount of distortion present in the system and responsive to the amount of distortion, autonomously alter or adjust the units of accuracy of information reported by the system. Such alteration or adjustment of units of accuracy may be performed based on an assessment of the distortion relative to a number of distortion thresholds. Responsive to the assessment, the volume dimensioning system can adjust a unit of accuracy in a representation of volume dimensioning related information.

BACKGROUND Field

This disclosure generally relates to volume dimensioning systems, andparticularly to systems and methods useful in the promoting compliancewith governmental or industry standard calibration guidelines.

Description of the Related Art

Volume dimensioning systems are useful for providing dimensional and/orvolumetric information related to three-dimensional objects. The objectsmay, for example take the form of parcels or packages intended fortransit via a carrier (e.g., courier) or other items intended fortransit. Dimensional and/or volumetric information is useful forexample, in providing users with accurate shipping rates based on theactual size and/or volume of the object being shipped. Dimensionaland/or volumetric information may be used by the carrier in selectingand scheduling appropriately sized vehicles and/or delivery routes. Theready availability of dimensional and/or volumetric information for allobjects within a carrier's network assists the carrier in ensuringoptimal use of available space in the many different vehicles andcontainers used in local, interstate, and international shipping.

Such may be of particular significant in today's economy where manybusinesses rely on “just in time” manufacturing. Typically, everysupplier in the supply chain must be able to ship necessary componentsor resources on demand or with very little lead time. Thus, efficienthandling of cargo is required. It does a supplier no good to have thedesired goods on hand, if the supplier cannot readily ship the desiredgoods.

Automating volume dimensioning can speed parcel intake, improve theoverall level of billing accuracy, and increase the efficiency of cargohandling. Unfortunately, parcels are not confined to a standard size orshape, and may, in fact, have virtually any size or shape. Additionally,parcels may also have specialized shipping and/or handling instructions(e.g., fragile, this side up) that must be followed during shipping orhandling to protect the objects during shipping.

Volume dimensioning devices are used throughout the package delivery andcarriage industry to provide a rapid way of measuring the overalldimensions of an object and, in some instances, to provide shippingrates for the object based on one or more classes of service.Historically, shipping rates were principally a function of an object'sweight—heavier objects were assigned higher shipping costs than lighterobjects. However, such a costing system failed to appreciate that volumethe volume occupied by an object also impacted shipping costs sincevehicles were not just limited in gross vehicle weight, but internalvolume as well. As a consequence shippers began establishing shippingrates using both volume and weight as factors considered in determiningthe ultimate shipping rate charged to a customer.

The concept of volume dimensioning factors the shipping volume of anobject into the overall shipping cost of an object. Thus, objects havinga relatively light weight but a relatively large physical volume mayhave a shipping cost that exceeds the shipping cost of a physicallysmaller, but heavier, object. The use of volume in determining shippingcosts increased the labor associated with package intake, since objectscould no longer simply be weighed and a cost assigned. Instead, toaccurately obtain a volume dimension, multiple dimensional measurementswere taken and used to determine the volume of the object. Once thevolume is determined, a shipping cost is assigned based on the measuredvolume and/or weight of the object. Thus, the shipping cost charged acustomer is a function of the weight of an object, the volume occupiedby the object, or both the weight of and the volume occupied by theobject. Automated volume dimensioning systems have replaced thelaborious and error prone derivation of an object's volume by manuallyobtaining multiple linear dimensions (e.g., the length, width, height,girth, etc.) of an object. The accuracy of a quoted shipping rate isthus dependent upon the accuracy with which an object can be dimensionedusing a volume dimensioning system.

There exists a need for new dimensioning systems that may accuratelyperform volume dimensioning of objects including parcels and packages aswell as other objects.

BRIEF SUMMARY

The Applicants have developed systems and methods useful for adjustingthe reported or displayed dimensional measurement accuracy andconsequently the reported or displayed shipping or cartage rate obtainedusing dimensional or volumetric data supplied by the volume dimensioningsystem. The systems and methods described herein take into considerationthe level of distortion (e.g., dimensional distortion, opticaldistortion, etc.) present in the image data provided by such automatedvolume dimensioning systems. In some instances, the system adjusts adimensional accuracy of a representation of volume dimensioninginformation (e.g., dimensions, cost based on the measured distortionpresent in the volume dimensioning system). Such may ensure that thedimensional and shipping cost data generated by the system is determinedusing the finest units of accuracy achievable given the current systemoperational parameters to reliably provide the most accurate shipping orcartage costs. Such systems and methods can be used to promote orfacilitate volume dimensioning system compliance with corporate,industry, or regulatory standards, best practices, or guidelines, forexample National Institute of Standards (NIST) Handbook 44-2012 Chapter5.58—“Multiple Dimension Measuring Devices”.

The systems and methods disclosed herein also facilitate the ongoing,operationally transparent, calibration of volume dimensioning systems.Such ongoing calibrations provide system users and consumers with adegree of confidence in the dimensional and shipping cost data providedby the volume dimensioning system and also provide an early indicationthat the system calibration can no longer be brought into compliancewith corporate, industry, or regulatory standards, best practices, orguidelines.

A volume dimensioning system may be summarized as including at least oneimage sensor that provides image data representative of a number ofimages of a field of view of the at least one image sensor; and acontrol subsystem communicatively coupled to the at least one imagesensor to receive the image data therefrom, the control subsystemincluding at least one nontransitory storage medium and at least oneprocessor, the at least one nontransitory storage medium which stores atleast one of information or processor executable instructions; and theat least one processor which: determines at least one distortion valueindicative of an amount of distortion in the images based at least inpart on at least a portion of a calibration pattern which appears in thefield of view of the at least one image sensor in at least a portion ofsome of the images, the calibration pattern having a set of definedcharacteristics; assesses the at least one distortion value relative toa number of distortion threshold values; and adjusts a unit of accuracyin a representation of volume dimensioning related information based atleast in part on the assessment of the at least one distortion valuerelative to the distortion threshold values.

The at least one processor may determine the at least one distortionvalue as at least one set of optical distortion values and at least oneset of dimensional distortion values, the set of optical distortionvalues representative of an optical contribution to distortion in theimage data and the set of dimensional distortion values representativeof a dimensional contribution to distortion in the image data. The atleast one processor may assess the at least one distortion valuerelative to a recalibration threshold value that represents distortioncorrectable via a self recalibration by the volume dimensioning system.The at least one processor may assess the at least one distortion valuerelative to a service required threshold value that representsdistortion that can only be corrected via a servicing of the volumedimensioning system by a service technician. The at least one processormay adjust the unit of accuracy in the representation of volumedimensioning related information in response to an assessment that theat least one distortion value exceeds the recalibration threshold valueand is below the service required threshold value. Responsive to thedetermination that the at least one distortion value is less than therecalibration threshold value, the at least one processor mayrecalibrate the volume dimensioning system to a fine unit of accuracy;and wherein responsive to the determination that the at least onedistortion value exceeds the recalibration threshold value and is belowthe service required threshold value, the at least one processor mayrecalibrate the volume dimensioning system to a coarse unit of accuracy.The processor may further produce an alert in response to an assessmentthat the at least one distortion value exceeds the service requiredthreshold value. The processor may further determine at least one of aset of calculated optical distortion correction factors or a set ofcalculated dimensional correction factors in response to an assessmentthat the at least one distortion value is within the recalibrationthreshold value and wherein the processor may further apply at least oneof the set of calculated optical distortion correction factors or theset of calculated dimensional correction factors to the image data indetermining the volume dimensioning related information. The processormay adjust a decimal place represented to adjust the unit of accuracy inthe representation of volume dimensioning related information. Theprocessor may adjust a dimensional unit of measurement represented toadjust the unit of accuracy in the representation of volume dimensioningrelated information. The processor may adjust a unit of currencyrepresented to adjust the unit of accuracy in the representation ofvolume dimensioning related information. The volume dimensioning systemmay further include an illumination subsystem communicably coupled tothe control subsystem, the illumination subsystem to at least partiallyilluminate the calibration pattern. The volume dimensioning system mayfurther include a support structure to receive at least the at least oneimage sensor such that when the at least one image sensor is received bythe support structure at least a portion of the pattern is within afield of view of the at least one image sensor. The system may be fixedor hand held. The at least one distortion value may be associated withat least one of data indicative of a date or data indicative of a timeand wherein the at least one distortion value and the respectiveassociated data indicative of a date or data indicative of a time may bestored in the non-transitory storage medium.

A volume dimensioning method may be summarized as including receiving byat least one dimensioning system processor image data representative ofa number of images in a field of view of at least one image sensor;determining by the at least one dimensioning system processor at leastone distortion value indicative of an amount of distortion in the imagesbased at least in part on at least a portion of a calibration patternwhich appears in the field of view of the at least one image sensor inat least some of the images, the calibration pattern having a set ofdefined characteristics; assessing by the at least one dimensioningsystem processor the at least one distortion value relative to a numberof distortion threshold values stored in a non-transitory storage mediumcommunicably coupled to the at least one dimensioning system processor;and adjusting by the at least one dimensioning system processor a unitof accuracy in a representation of volume dimensioning relatedinformation based at least in part on the assessment of the at least onedistortion value relative to the distortion threshold values.

Assessing by the at least one dimensioning system processor the at leastone distortion value relative to a number of distortion threshold valuesmay include determining the at least one distortion value as at leastone set of optical distortion values and at least one set of dimensionaldistortion values; wherein the set of optical distortion valuesrepresents an optical contribution to distortion in the image data; andwherein the set of dimensional distortion values represent a dimensionalcontribution to distortion in the image data. Assessing by the at leastone dimensioning system processor the at least one distortion valuerelative to a number of distortion threshold values may includeassessing the at least one distortion value relative to a recalibrationthreshold value representing distortion correctable via a recalibrationof the volume dimensioning system. Assessing by the at least onedimensioning system processor the at least one distortion value relativeto a number of distortion threshold values may include assessing the atleast one distortion value relative to a service required thresholdvalue representing distortion not correctable via recalibration of thevolume dimensioning system. Assessing by the at least one dimensioningsystem processor the at least one distortion value relative to a numberof distortion threshold values may include assessing the at least onedistortion value to fall between the recalibration threshold value andthe service required threshold value, representing distortioncorrectable via a recalibration of the volume dimensioning system.Adjusting a unit of accuracy in a representation of volume dimensioningrelated information based at least in part on the assessment of the atleast one distortion value relative to the distortion threshold valuesmay include recalibrating the volume dimensioning system to a fine unitof accuracy responsive to an assessment that the at least one distortionvalue relative to the recalibration threshold value indicates adistortion correctable via recalibration; recalibrating the volumedimensioning system to a coarse unit of accuracy responsive to anassessment that the at least one distortion value falls between therecalibration threshold value and the service required threshold value;and generating an alert responsive to an assessment that the at leastone distortion value relative to the service required threshold valueindicates a distortion not correctable via recalibration. The volumedimensioning method may further include, responsive to the determinationthat the at least one distortion value is within the recalibrationthreshold value, determining by the at least one dimensioning systemprocessor at least one of a set of calculated optical distortioncorrection factors or a set of calculated dimensional correctionfactors; and applying at least one of the set of calculated opticaldistortion correction factors or the set of calculated dimensionalcorrection factors to the image data in determining the volumedimensioning related information.

A volume dimensioning controller may be summarized as including at leastone input communicably coupled to at least one processor, the at leastone input to receive image data representative of a number of images ofa field of view of at least one image sensor; and at least one processorcommunicably coupled to the at least one non-transitory storage medium,the at least one processor to: determine at least one distortion valueindicative of an amount of distortion in the images based at least inpart on at least a portion of a calibration pattern which appears in thefield of view of the at least one image sensor in at least some of theimages, the calibration pattern having a set of defined characteristics;assess the at least one distortion value relative to a number ofdistortion threshold values stored in the non-transitory storage medium;and adjust a unit of accuracy in a representation of volume dimensioningrelated information based at least in part on the assessment of the atleast one distortion value relative to the distortion threshold values.

The at least one processor may determine the at least one distortionvalue as at least one set of optical distortion values and at least oneset of dimensional distortion values, the set of optical distortionvalues representative of an optical contribution to distortion in theimage data and the set of dimensional distortion values representativeof a dimensional contribution to distortion in the image data. The atleast one processor may assess the at least one distortion valuerelative to a recalibration threshold value that represents distortioncorrectable via a self recalibration by the volume dimensioning system.The at least one processor may assess the at least one distortion valuerelative to a service required threshold value that representsdistortion that can only be corrected via a servicing of the volumedimensioning system by a service technician. The at least one processormay adjust the unit of accuracy in the representation of volumedimensioning related information in response to an assessment that theat least one distortion value exceeds the recalibration threshold valueand is below the service required threshold value. Responsive to thedetermination that the at least one distortion value is less than therecalibration threshold value, the at least one processor mayrecalibrate the volume dimensioning system to a fine unit of accuracy;and wherein responsive to the determination that the at least onedistortion value exceeds the recalibration threshold value and is belowthe service required threshold value, the at least one processor mayrecalibrate the volume dimensioning system to a coarse unit of accuracy.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

In the drawings, identical reference numbers identify similar elementsor acts. The sizes and relative positions of elements in the drawingsare not necessarily drawn to scale. For example, the shapes of variouselements and angles are not drawn to scale, and some of these elementsare arbitrarily enlarged and positioned to improve drawing legibility.Further, the particular shapes of the elements as drawn, are notintended to convey any information regarding the actual shape of theparticular elements, and have been solely selected for ease ofrecognition in the drawings.

FIG. 1 is a block diagram of an example volume dimensioning system,according to one illustrated embodiment.

FIG. 2A is a perspective view of a volume dimensioning system displayingone example of the effects of optical distortion, according to oneillustrative embodiment.

FIG. 2B is a perspective view of a volume dimensioning system displayingone example of the effects of dimensional distortion, according to oneillustrative embodiment.

FIG. 3 is a perspective view of an example image sensor received by astand member and having a reference pattern disposed in at least aportion of the field of view of the image sensor, according to oneillustrative embodiment.

FIG. 4A is a perspective view of an example volume dimensioning systemreporting dimensions to a first unit of accuracy based at least in parton at least one determined distortion value, according to oneillustrative embodiment.

FIG. 4B is a perspective view of an example volume dimensioning systemreporting dimensions to a second unit of based at least in part on atleast one determined distortion value, according to one illustrativeembodiment.

FIG. 5 is a flow diagram showing a high level method of operation of avolume dimensioning system including the determination of at least onedistortion value and one or more sets of distortion correction factors,according to one illustrated embodiment.

FIG. 6 is a flow diagram showing a low level method of operation of avolume dimensioning system including an assessment of at least one setof optical distortion values and at least one set of dimensionaldistortion values, according to one illustrative embodiment.

FIG. 7 is a flow diagram showing a high level method of operation of avolume dimensioning system incorporating the storage and reporting ofhistorical distortion values or correction factors, according to oneillustrated embodiment.

DETAILED DESCRIPTION

In the following description, certain specific details are set forth inorder to provide a thorough understanding of various disclosedembodiments. However, one skilled in the relevant art will recognizethat embodiments may be practiced without one or more of these specificdetails, or with other methods, components, materials, etc. In otherinstances, well-known structures associated with volume dimensioningsystems, correction of optical and dimensional distortion in single andcompound lens devices, wired, wireless and optical communicationssystems, and/or automatic data collection (ADC) readers have not beenshown or described in detail to avoid unnecessarily obscuringdescriptions of the embodiments.

Unless the context requires otherwise, throughout the specification andclaims which follow, the word “comprise” and variations thereof, suchas, “comprises” and “comprising” are to be construed in an open,inclusive sense, that is as “including, but not limited to.”

Reference throughout this specification to “one embodiment” or “anembodiment” means that a particular feature, structure or characteristicdescribed in connection with the embodiment is included in at least oneembodiment. Thus, the appearances of the phrases “in one embodiment” or“in an embodiment” in various places throughout this specification arenot necessarily all referring to the same embodiment. Furthermore, theparticular features, structures, or characteristics may be combined inany suitable manner in one or more embodiments.

As used in this specification and the appended claims, the singularforms “a,” “an,” and “the” include plural referents unless the contentclearly dictates otherwise. It should also be noted that the term “or”is generally employed in its broadest sense, that is as meaning “and/or”unless the content clearly dictates otherwise.

The headings and Abstract of the Disclosure provided herein are forconvenience only and do not interpret the scope or meaning of theembodiments.

FIG. 1 shows a volume dimensioning system 100, according to oneillustrated embodiment.

The volume dimensioning system 100 includes a camera subsystem 102 andcontrol subsystem 104. The volume dimensioning system 100 optionallyincludes one or more of: a user interface (UI) subsystem 106; acommunications subsystem 108 and/or an automatic data collection (ADC)subsystem 110. The various subsystems 102-110 may be communicativelycoupled by one or more couplers (e.g., electrically conductive paths,wires, optical fibers), for example via one or more buses 112 (only oneshown) and/or control lines 114 (only two shown). The buses 112, orother couplers, may include power buses or lines, data buses,instruction buses, address buses, etc., which allow operation of thevarious subsystems 102-110 and interaction or intercommunicationtherebetween. The various subsystems 102-110 are each discussed in turn,below. While various individual components are generally easilycategorizable into one or another of the subsystems, some components maybe optionally implemented in one or two or more of the subsystems102-110. Thus, some components may be illustrated in FIG. 1 as part oftwo or more subsystems 102-110. Alternatively, some of the componentsillustrated in FIG. 1 as discrete components in two or more subsystems102-110 may be present as a single component within a single subsystem102-110.

The camera subsystem 102 includes an optional illumination subsystem 116to provide or emit electromagnetic illumination outward from the volumedimensioning system 100 into an environment containing a target object(not shown in FIG. 1) and a sensor subsystem 118 to receive illuminationreturned (e.g., reflected, fluoresced) from at least the target object.

The illumination subsystem 116 includes an illumination device 120. Theillumination device 120 may take the form of an array of individuallyaddressable or controllable elements, and also may have a variety offorms capable of producing electromagnetic energy having a spectralcontent useful for image collection by the sensor subsystem 118. Theillumination subsystem 116 will typically include an illumination driver122 which is coupled to control the individually addressable orcontrollable elements of the illumination device 120. Alternatively, theillumination device 120 may be controlled directly by the controlsubsystem 104 without the use of a dedicated illumination driver 122.

In particular, the illumination device 120 is controlled to produce oremit modulated electromagnetic energy in a number of wavelengths orranges of wavelengths. For instance, illumination may includeelectromagnetic energy of wavelengths in an optical range or portion ofthe electromagnetic spectrum including wavelengths in a human-visiblerange or portion (e.g., approximately 390 nm-750 nm) and/or wavelengthsin the near-infrared (NIR) (e.g., approximately 750 nm-1400 nm) orinfrared (e.g., approximately 750 nm-1 mm) portions and/or thenear-ultraviolet (NUV) (e.g., approximately 400 nm-300 nm) orultraviolet (e.g., approximately 400 nm-122 nm) portions of theelectromagnetic spectrum. The particular wavelengths are exemplary andnot meant to be limiting. Other wavelengths of electromagnetic energymay be employed.

The sensor subsystem 118 includes an image transducer or image sensor124, typically a two-dimensional array of photo-sensitive orphoto-responsive elements, for instance a two-dimensional array ofphotodiodes or a two-dimensional array of charge coupled devices (CODs).The sensor subsystem 118 may optionally include a buffer 125communicatively coupled to the image sensor 124 to receive or otherwiseacquire image data measured, captured or otherwise sensed or acquired bythe image sensor 124. The buffer 125 may comprise a non-transitorystorage medium capable of temporarily storing image data until the imagedata is further processed by the volume dimensioning system 100. In atleast some instances, the sensor subsystem 118 can include one or moresensors, systems, or devices for reading or scanning one or more opticalmachine readable symbols or radio frequency machine readable devicessuch as radio frequency identification (RFID) tags. Some possiblysuitable systems are described in U.S. patent application Ser. No.12/638,616, filed Dec. 15, 2009 and published as U.S. patent applicationpublication no. US 2010-0220894, which is incorporated by referenceherein in its entirety to the extent the subject matter therein does notcontradict or conflict with the subject matter of the instantapplication.

The sensor subsystem may further include one or more distancedetermination sensors (not shown in FIG. 1) useful in measuring orotherwise determining the distance between the volume dimensioningsystem 100 and one or more objects within the field of view of the imagesensor 124. Such distance detection sensors can include one or moretime-of-flight sensors, sonar sensors, or similar. In at least someinstances the image sensor 124 may advantageously include one or moredistance determination features, for example parallax measured acrossall or a portion of the image sensor 124.

The control subsystem 104 includes one or more processors 126, forexample one or more microprocessors (one shown) 126 a, digital signalprocessors (DSP—one shown) 126 b, application specific integratedcircuits (ASIC), programmable gate arrays (PGA), programmable logiccontrollers (PLC), or the like. While the DSP 126 b may be considered orprovided or packaged as part of the control subsystem 104, the DSP 126 bmay in some applications be may be considered or provided or packaged aspart of the camera subsystem 102.

The control subsystem 104 includes at least one non-transitory storagemedia 130. For example, the control subsystem 104 may includenonvolatile memory, for instance read only memory (ROM) or NAND Flashmemory 130 a. Additionally or alternatively, all or a portion of the atleast one non-transitory storage media 130 may include volatile memory,for instance dynamic random access memory (ROM) 130 b. The at least onenon-transitory storage media 130 may store one or more computer- orprocessor-executable instructions or data, useful in causing themicroprocessor, DSP or other microcontroller to perform dimensionalfunctions, volumetric functions, volume dimensioning functions, shippingcost calculation functions, or combinations thereof, for example byexecuting the various methods described herein.

In some instances the at least one non-transitory storage media 130 maystore or otherwise retain a number of distortion values indicative ofthe quantitative or qualitative degree of distortion present in theimage data provided by the volume dimensioning system 100. Suchdistortion may be present as an optical distortion, a dimensionaldistortion, or any other type of distortion including chromaticdistortion that causes deviations between the image data and the scenewithin the field of view of the sensor subsystem 118. In yet otherinstances, the at least one non-transitory storage media 130 may storeor otherwise retain a plurality of historical distortion values, such asa plurality of optical or dimensional distortion values that permit thehistorical trending of the optical or dimensional distortion values.Such historical data can also play a helpful role in demonstrating anongoing compliance with one or more corporate, industry, or regulatoryguidelines, best practices, or standards. In at least some instances,the at least one non-transitory storage media 130 can store or otherwiseretain one or more sets of distortion correction factors useful inreducing or eliminating one or more forms of distortion present in theimage data provided by the volume dimensioning system 100.

The optional UI subsystem 106 may include one or more user interfacecomponents which provide information to a user or allow a user to inputinformation or control operation of the volume dimensioning system 100.

For example, the UI subsystem 106 may include a display 132 to visuallyprovide information or control elements to the user. The display 132may, for example, take the form of a liquid crystal display (LCD) panel.The display 132 may, for example, take the form of a touch sensitivedisplay, allowing the display of user selectable icons (e.g., virtualkeypad or keyboard, graphical user interface or GUI elements) inaddition to the display of information. The display 132 may be coupledto the control subsystem 104 via a display driver 134 or similarcomponent. The display driver 134 may control the presentation ofinformation and icons on the display 132. The display driver 134 mayadditionally process signals indicative of user inputs made via thedisplay 132.

The UI subsystem 106 may optionally include a physical keypad orkeyboard 136, which allows a user to enter data and instructions orcommands. The physical keypad or keyboard 136 may be integral to ahousing (not shown) of the volume dimensioning system 100.Alternatively, the optional physical keypad or keyboard 136 may beseparate from the housing, communicatively coupled thereto via awireless connection or wired connection for instance a Universal SerialBus (USB®) interface.

The UI subsystem 106 may optionally include a speaker 138 to provideaudible information, cues and/or alerts to a user. The UI subsystem 106may optionally include a microphone 140 to receive spoken information,instructions or commands from a user.

The communications subsystem 108 may include one or more wirelesscommunications components and/or one or more wired communicationscomponents to allow communications with devices external from the volumedimensioning system 100.

For example the communications subsystem 108 may include one or moreradios (e.g., transmitters, receivers, transceivers) 142 and associatedantenna(s) 144. The radio(s) 142 may take any of a large variety offorms using any of a large variety of communications protocols, forinstance IEEE 802.11, including WI-FI®, BLUETOOTH®, various cellularprotocols for instance CDMA, TDMA, EDGE®, 3G, 4G, GSM.

Also for example, the communications subsystem 108 may include one ormore communications ports 146. The communications ports 146 may take anyof a large variety of forms, for example wired communications ports forinstance ETHERNET® ports, USB® ports, FIREWIRE® ports, THUNDERBOLT®ports, etc. The communications ports 146 may even take the form ofwireless ports, for instance an optical or radio frequency transceiver.

The ADC subsystem 110 may include one or more ADC readers to performautomatic data collection activities, for instance with respect to atarget object.

For example, the ADC subsystem 110 may include a radio frequencyidentification (RFID) reader or interrogator 148 and associated antenna150 to wireless read and/or write to wireless transponders (e.g., RFIDtags or transponders) (not shown). Any of a large variety of RFIDreaders or interrogators 148 may be employed, including fixed orstationary RFID readers or portable or handheld RFID readers. RFIDreader(s) 148 may be used to read information from a transponderphysically or at least proximally associated with a target object (notshown in FIG. 1). Such information may, for instance, include recipientinformation including an address and/or telephone number, senderinformation including an address and/or telephone number, specifichandling instructions (e.g., fragile, keep a give side up, temperaturerange, security information). The RFID reader 148 may also writeinformation to the transponder, for instance information indicative of atime and/or place at which the transponder was read, creating a trackingrecord.

Also for example, the ADC subsystem 110 may include a machine-readablesymbol reader 152 to wireless read machine-readable symbols (e.g.,one-dimensional or barcode symbols, two-dimensional or matrix codesymbols) (not shown). Any of a large variety of machine-readable symbolreaders 152 may be employed. For example, such may employ scanner basedmachine-readable symbol readers 152 such as those that scan a point oflight (e.g., laser) across a symbol and detector light returned from thesymbol, and decoding information encoded in the symbol. Also forexample, such may employ imager based machine-readable symbol readers152 such as those that employ flood illumination (e.g., LEDs) of asymbol, detect or capture an image of the symbol, and decode informationencoded in the symbol. The machine-readable symbol reader(s) 152 mayinclude fixed or stationary machine-readable symbol readers or portableor handheld machine-readable symbol readers. The machine-readable symbolreader(s) 152 may be used to read information from a machine-readablesymbol physically or at least proximally associated with a targetobject. Such information may, for instance, include recipientinformation including an address and/or telephone number, senderinformation including an address and/or telephone number, specifichandling instructions (e.g., fragile, keep a give side up, temperaturerange, security information).

While not illustrated, the volume dimensioning system 100 may include aself contained, discrete source of power, for example one or morechemical battery cells, ultracapacitor cells and/or fuel cells. Whilealso not illustrated, the volume dimensioning system 100 may include arecharging circuit, for example to recharge secondary chemical batterycells. Alternatively or additionally, the volume dimensioning system 100may be wired to an external power source, such as mains, residential orcommercial power.

FIGS. 2A and 2B illustrate different types of distortion visible as adeviation between the pattern image data 212, 222 within the respectivesystems 100 when compared the calibration or reference pattern 202. Thereference pattern 202 is disposed within the field of view 210 of the atleast one image sensor 124 and comprises alternating squares of whiteareas 204 and color areas 206.

The dimensions of the reference pattern 202 are defined, fixed, andknown by the volume dimensioning system 100 prior to imaging. Thisallows the volume dimensioning system 100 to analyze pattern image data212, 222 containing at least a portion of the reference pattern 202 toassess or quantify the distortion present in the image and to generateat least one distortion value indicative of the distortion. Thedistortion may be global throughout the image or may be localized withdifferent portions of the image exhibiting different types or amounts ofdistortion.

FIG. 2A illustrates the effect of an optical distortion that renders theimage with a “pincushion” distortion where the white and colored squares204, 206 in the original pattern 202 are reproduced in the pattern imagedata 212 as generally diamond shaped white and colored areas 214, 216,respectively. Although the pincushion distortion illustrated in FIG. 2Ais exaggerated, it can be appreciated that any such or similar opticaldistortion may adversely affect to some degree the volume dimensioningsystem's ability to accurately determine dimensional and volumetricdata. Such inaccurate dimensional and volumetric data can adverselyaffect the system's ability to provide accurate shipping volumes andshipping rates to carriers and consumers.

FIG. 2B illustrates the effect of a dimensional distortion along asingle (horizontal) axis where the white and colored squares 204, 206 inthe reference pattern 202 are reproduced in the pattern image data 222as generally rectangular shaped white and colored areas 224, 226,respectively.

Disproportionate compression of the image data along one axis (e.g.,along the x-axis 230 in FIG. 2B) causes the dimensional distortion seenin the pattern image data 222. Conversely, disproportionate extension ofthe image data along two or more axes may result in both dimensional andgeometric distortion of the reference pattern 202. Although thedimensional distortion appearing in FIG. 2B is exaggerated, it can beappreciated that any such or similar dimensional or geometric distortioncan also adversely affect the volume dimensioning system's ability toaccurately determine dimensional and volumetric data. Such inaccuratedimensional and volumetric data can adversely affect the system'sability to provide accurate shipping volumes and shipping rates tocarriers and consumers. Although shown in two different figures forclarity and ease of discussion, optical and dimensional distortion,along with other forms of distortion such as color or chromaticaberration or distortion, may appear in image data produced by a volumedimensioning system 100. Such combinations further complicate theaccurate determination of dimensional or volumetric informationtherefrom. Uncorrected, such optical and dimensional distortion in theimage can cause the calculation or propagation of erroneous dimensionalinformation and consequently volumetric information and volume-basedshipping cost information.

Optical distortion may be present in the image data received from thesensor subsystem 118 in many forms. Typical forms of optical distortionpresent in image data can include radial distortion, chromatic orspherical aberration, linear distortion, geometric distortion, andcombinations thereof. Such optical distortion may not necessarily be aconsequence of a latent defect in the sensor subsystem 118 but may beinherent in the design or manufacture of the optics used to provide thesensor subsystem 118 or characteristic of the image processing hardware,firmware, or software employed by the volume dimensioning system 100.Such optical distortion may variously be referred to as pincushiondistortion, barrel distortion, or mustache distortion depending on thevisual appearance of the distortion present in the displayed patternimage data 212, 222. Regardless of the cause, the presence of distortionin the image data compromises the ability of the volume dimensioningsystem 100 to accurately determine dimensional or volumetric data for anobject. Uncorrected, such optical and dimensional distortion mayadversely impact the accuracy of the shipping costs provided by thevolume dimensioning system 100 and also may hinder a shipper's abilityto schedule and load shipping containers, trucks, railcars, or the likebased on the dimensional and volumetric data.

In some instances, optical distortion may be present but non-uniformlydistributed across an image. Such distortion may result in a portion ofan image suffering little or no optical distortion while other portionsof the same image suffer significant distortion. For example, littleoptical distortion may be present in the center portion of an imagewhile all or a portion of the periphery of the same image may suffer amuch greater degree of optical distortion. In other instances a firsttype of distortion may be distributed more-or-less uniformly across theimage while a second type of distortion may be present in one or morelocalized areas. In yet other instances, an object of dimensionalinterest may lie within only a portion of an optically distorted imagecaptured by the image sensor. In such instances, it may be advantageousto locally correct the distortion present in the area of the image inwhich the object of dimensional interest lies. In at least someinstances, if the type and extent of such local distortion present in animage can be assessed or is of a known type, extent, and/or magnitude,then local dimensional correction may be possible within the image. Theability to locally correct distortion present in an image advantageouslyeliminates the application of such distortion correction in portions ofthe image having where such distortion is not present.

Although the reference pattern 202 is depicted as a checkerboard, anynumber of machine recognizable indicia including one or moremachine-readable symbols, machine-readable patterns, calibrationpatterns, calibration targets, calibration points, or the like may besimilarly employed as a tool for assessing the distortion (e.g., amount,type, location) present in the image data. Physical parametersassociated with the reference pattern 202 can be provided to the volumedimensioning system 100 either as one or more factory settings (e.g.,preloaded values placed into the read only portion of the non-transitorystorage medium) or communicated to the volume dimensioning system (e.g.,via a network, Bluetooth, or similar connection). All or a portion ofsuch physical parameters may include color information associated withthe reference pattern 202 including the overall reference pattern size,the size of the white areas 204, the size of the colored areas 206, orcombinations thereof. All or a portion of such physical parameters mayinclude the spatial or geometric relationship between the various whiteand colored areas 204, 206 in the reference pattern 202. All or aportion of such physical parameters may include information encoded intoone or more regions or portions of the reference pattern 202 in the formof one or more machine readable indicia or symbols. Pattern image data212, 214 is used by the at least one processor 126 to detect andquantify the distortion (e.g., optical or dimensional distortion)present in the image data using the one or more known physicalparameters. The quantity of distortion present may be expressed as atleast one distortion value. In at least some instances, all or a portionof the reference pattern 202 may be useful in calibrating the volumedimensioning system 100.

In at least some instances, the entire electromagnetic spectrumreflected or otherwise returned from the reference pattern 202 may beused by the at least one processor 126 to determine all or a portion ofthe at least one distortion value. In other instances, only a portion ofthe electromagnetic spectrum reflected or otherwise returned from thereference pattern 202 may be used by the at least one processor 126 todetermine the at least one distortion value. In some instances, thereference pattern 202 may return pattern image data unique to theelectromagnetic spectrum illuminating the reference pattern 202 (e.g.,the pattern image data returned in a near-ultraviolet spectrum maydiffer from that returned in a visible spectrum). Portions of theelectromagnetic spectrum used by the at least one processor 126 mayinclude, but are not limited to, the near ultraviolet portion of theelectromagnetic spectrum, the near infrared portion of theelectromagnetic spectrum, one or more portions of the visibleelectromagnetic spectrum, or any portion of combination thereof.

Although the entire reference pattern 202 is shown within the field ofview 210 of the image sensor 124 in both FIGS. 2A and 2B, only a portionof the reference pattern 202 need be within the field of view 210 of theimage sensor 124 to permit the at least one processor 126 to determinethe at least one distortion value indicative of the distortion presentin the pattern image data 212, 222. Additionally, only a portion of thereference pattern 202 need be within the field of view 210 of the imagesensor 124 to permit the at least one processor 126 to determine anumber of sets of distortion correction factors (e.g., one or more setsof optical or dimensional distortion correction factors) that are usefulin reducing or eliminating the effect of distortion on the accuracy ofdimensional, volumetric, volume dimensioning or cost data provided bythe volume dimensioning system 100.

Identification data may in some instances be created, generated orotherwise provided by the at least one processor 126 and associated withthe at least one determined distortion value. Such identification datamay include chronological data such as data indicative of the date orthe time at which the at least one distortion value was obtained,calculated, or otherwise determined by the at least one processor 126.Such identification data may include chronological data such as dataindicative of the date or the time at which one or more sets ofdistortion correction factors are determined by the at least oneprocessor 126. Such identification data may include chronological dataassociated with system events (e.g., distortion value determination,distortion correction determination, system calibration, a change insystem units of accuracy, a change in system configuration, etc.) thatare recommended or required for compliance with one or more corporate,industry, or regulatory guidelines, best practices, or standards.

The determined at least one distortion value along with the respectiveassociated identification data may be at least partially stored in theat least one non-transitory storage media 130. Maintaining a history ofthe determined at least one distortion value may advantageously providethe ability for the one or more processors 126 to predict expectedfuture distortion values and to detect sudden or unexpected changes inthe level or magnitude of the determined at least one distortion value.Sudden changes in the at least one distortion value may, for example,indicate an unexpected change in performance of the volume dimensioningsystem 100. The ability to predict future expected distortion valuesmay, for example, be useful in providing a predicted replacementinterval or an expected remaining service life for the volumedimensioning system 100.

In at least some instances, the volume dimensioning system 100 cangenerate an output that includes both identification data and theassociated at least one distortion value either as a visible output onuser interface 132 or as a data output transmitted via the communicationsubsystem 108 to an external device such as a non-transitory datastorage location on a local network or in the cloud or an externaldisplay device such as a printer or similar data output device.

At least some instances, the at least one processor 126 can calculate orotherwise determine one or more sets of distortion correction factors(e.g., one or more sets of optical distortion factors or one or moresets of dimensional distortion factors) based in whole or in part on thedetermined at least one distortion value. When within a first set ofdistortion threshold values, the volume dimensioning system 100 may usethe distortion correction factors to reduce or even eliminate theeffects of distortion, improving the dimensional, volumetric, andresultant shipping cost calculation capabilities of the volumedimensioning system 100.

The at least one processor 126 may determine the distortion correctionfactors using one or more numerical distortion correction methods.Numerical distortion correction methods may, for example, includeBrown's distortion model or other similar mathematical distortioncorrection methods or schemes. One or more graphical distortioncorrection methods may also be used alone or in cooperation with one ormore numerical distortion correction methods.

In some instances, the at least one processor 126 may use the entireelectromagnetic spectrum of the image provided by the sensor subsystem118 to determine all or a portion of the one or more distortioncorrection factors. In other instances, the at least one processor mayuse a portion of the electromagnetic spectrum of the image provided bythe sensor subsystem 118 to determine the one or more distortioncorrection factors. The use of sets of distortion correction factors inone or more portions of the electromagnetic spectrum may in someinstances advantageously provide the ability to partially or completelycorrect at least a portion of the chromatic aberration present in theimage data provided by the sensor subsystem 118.

Dimensional distortion such as that shown in FIG. 2B may cause thegenerally square areas of one color (e.g., white 214) and areas of asecond color (e.g., black 216) within the reference pattern 202 toappear as compressed rectangular or trapezoidal areas in the patternimage data 222. Such dimensional or geometric distortion may be evenlyor unevenly distributed along one or more principal axes. For example,in FIG. 2B dimensional distortion may be present along the x-axis 222,the y-axis 224, or along both axes. Some or all of the dimensionaldistortion may be linear or nonlinear. In addition, although illustratedalong two principal axes, dimensional distortion may be present along athird axis as well. In the example shown in FIG. 2B, dimensionaldistortion is present only along the x-axis 230, wherein each of therespective areas of one color (e.g., white 214) and areas of the othercolor (e.g., black 216) have been reduced in width along the x-axis 230by approximately 40%. Conversely, little or no dimensional distortionhas occurred along the y-axis 232.

In at least some instances the distortion present in the image data mayinclude both optical and dimensional distortion. In such instances theone or more processors 126 may calculate multiple distortion valuesincluding at least one optical distortion value indicative of the levelof optical distortion present in the image data and at least onedimensional distortion value indicative of the level of dimensionaldistortion present in the image data. The at least one opticaldistortion value and the at least one dimensional distortion value maybe stored or otherwise retained individually within the non-transitorystorage media 130 or alternatively may be combined to provide at leastone combined distortion value reflective of both the optical anddimensional distortion present in the image data. Using one or morecalibration parameters of the reference pattern 202 and based on thedetermined at least one distortion value, the one or more processors 126can determine or otherwise generate one or more sets of distortioncorrection factors. Such sets of distortion correction factors caninclude one or more sets of optical distortion correction factors, oneor more sets of dimensional distortion correction factors, orcombinations thereof. The one or more sets of distortion correctionfactors can be wholly or partially stored or otherwise retained in theat least one non-transitory storage media 130. The one or more sets ofdistortion correction factors are used by the at least one processor 126to reduce or eliminate the effects of distortion present in the imagedata on the determined dimensional, volumetric, volume dimensional, orcost data provided by the volume dimensioning system 100. Additionally,the one or more sets of distortion correction factors may be used to bythe at least one processor 126 to correct the image data prior to usingthe image data to provide an output on the display 132. The volumedimensioning system 100 can determine the at least one distortion valueand one or more sets of distortion correction factors on a regular orirregular basis. For example, in some instances, the volume dimensioningsystem 100 can determine the at least one distortion value when thereference pattern 202 falls within the field of view of the at least onesensor 124 and the system 100 is not actively volume dimensioning anobject. Such may occur when the volume dimensioning system 100 is placedin a defined location for example returned to a cradle or stand. Inother instances, the routine range of motion may bring the referencepattern 202 within the field of view of the at least one sensor 124 asthe volume dimensioning system is moved or displaced. For example, thereference pattern 202 may appear in the field of view of the at leastone image sensor 124 when the volume dimensioning system 110 is movedfrom a “storage” position or location to a “ready” position or location,or from a “ready” position or location to a “storage” position orlocation. In yet other instances, the volume dimensioning system 100 mayprovide one or more human perceptible indicators or signals that prompta user to at least partially align the volume dimensioning system 100with the reference pattern 202 to permit the system to perform adistortion correction or calibration.

In other instances, determination of the at least one distortion valueand optionally the determination of the at least one set of distortioncorrection factors may occur as a portion of the volume dimensioningsystem 100 calibration routine. For example, in some instances, the atleast one distortion value may be determined prior to the performance ofa volume dimensioning system calibration to improve or otherwise enhancethe level of accuracy of the calibration. In some instances, suchdistortion correction or calibration routines may be time-based andconducted at regular or irregular intervals. In other instances, suchdistortion correction or calibration routines may be performance relatedand conducted based upon one or more measured system performanceparameters. In yet other instances, such distortion correction orcalibration routines may be time and performance based to comply withone or more corporate, industry, or regulatory standards, bestpractices, or guidelines.

Advantageously, the ability to detect the presence of distortion presentin the image data, to quantify the distortion using at least onedistortion value, to optionally determine one or more sets of distortioncorrection factors, and to optionally incorporate both into a volumedimensioning system calibration procedure reduces the likelihood of thevolume dimensioning system 100 providing erroneous linear, volumetric,or shipping cost information. Such periodic detection and quantificationof distortion present in the image data may be conducted on an automatic(i.e., system generated) or manual (i.e., at user discretion) basis atregular or irregular intervals.

FIG. 3 shows a volume dimensioning system 100 that has been received byan exemplary support member 302 such as a stand or cradle. In at leastsome instances, at least a portion of a reference pattern 202 appearswithin the field of view 210 of the image sensor 124 when the volumedimensioning system 100 is received by the support member 302. Thesupport member 302 may include a base member 304 to increase stabilityof the support member. Although depicted in FIG. 3 as supporting ahandheld or portable volume dimensioning system 100, in some instancesthe support member 302 may receive only a portion, for example thesensor subsystem 118, of a larger or even stationary volume dimensioningsystem 100. The reference pattern 202 may be formed as a portion of thebase member 304, separate from the base member 304, or as a member thatis detachably attached to the base member 304.

The volume dimensioning system 100 may also include one or more sensors(not visible in FIG. 3) to detect the presence of the support member302. Example sensors may include without limitation, one or more opticalsensors, one or more ultrasonic sensors, one or more proximity sensors,or similar. Such sensors may provide one or more input signals to the atleast one processor 126 indicating receipt of the volume dimensioningsystem 100 by the support member 302. In at least some instances, upondetection of the signal indicating receipt by the support member 302 theat least one processor 126 can initiate the capture of image data by thesensor subsystem 118. Since the reference pattern 202 lies within thefield of view of the at least one image sensor 124, the image data soacquired may be used to determine at least one distortion value,calibrate the system 100, calculate one or more sets of distortioncorrection factors, or any combination thereof. In some instances,pattern image data from the sensor subsystem 118 received by the supportmember 302 may be wiredly or wirelessly communicated to a remote volumedimensioning system 100.

In at least some instances the reference pattern 202 can be formed onthe base 304 or on a rigid or flexible member that is operably coupledor otherwise attached to the base member 304. The reference pattern 202may be formed in different colors, materials, embossings, debossings,textures, engravings, or similar. In some instances, the referencepattern 202 may include one or more inscriptions, logos, designs,trademarked images, or the like. In at least some instances all or aportion of the reference pattern 202 and the base member 304 may bedetached and mounted remotely from the support member 302. For example,in at least some instances the reference pattern 202 may be mounted on avertical surface such as a wall or similar partition.

In at least some situations, when the volume dimensioning system 100 isreceived by the support member 302 the sensor subsystem 118 mayautonomously provide pattern image data including at least the portionof the reference pattern 202 to the at least one processor 126.Autonomous provision of image data by the sensor subsystem 118 to the atleast one processor 126 may occur at regular or irregular intervals.Autonomous collection of pattern image data may permit a more frequentupdating of the at least one distortion value or the one or more sets ofdistortion correction factors than a manually initiated collection ofpattern image data since such autonomous collection may occur at timeswhen the volume dimensioning system 100 is not in active use. Thepattern image data so acquired allows the at least one processor 126 todetermine the at least one distortion value using the known referencepattern 202 calibration parameters. Access to pattern image data alsooptionally permits the at least one processor 126 to determine the oneor more sets of distortion correction factors. Providing the at leastone processor 126 with the ability to determine the at least onedistortion value and the sets of distortion correction factors while thevolume dimensioning system 100 is not in active use may advantageouslyincrease the overall accuracy of the dimensional, volumetric, and costinformation provided by the system 100.

FIG. 4A provides a perspective view of an illustrative volumedimensioning system 100 a where the at least distortion value within afirst threshold permitting the use of a fine unit of accuracy (e.g., 1mm depicted in FIG. 4A) to determine the dimensional, volumetric, andcost data associated with object 402 a. FIG. 4B provides a perspectiveview of an illustrative volume dimensioning system 100 b now where theat least distortion value is not within the first threshold permittingthe use of a fine unit of accuracy and, as a consequence, the at leastone processor 126 has autonomously shifted to the use of a coarse unitof accuracy (e.g., 1 cm depicted in FIG. 4B) to determine thedimensional, volumetric, and cost data associated with object 402 b.

Although the object 402 a is depicted as a cubic solid for simplicityand ease of illustration, it should be understood that similarprinciples as described below will apply to any object placed within thefield of view of the volume dimensioning system 100. Object 402 a isillustrated as having actual dimensions of 11.1 cm in length, 6.3 cm inwidth, and 15.6 cm in height. Such an object may be representative of acommonly encountered shipping container such as a cardboard box. Priorto placement of the object 402 a in the field of view 210 of the imagingsensor 124, the volume dimensioning system 100 a has determined throughthe use of a reference pattern 202 (not shown in FIG. 4A) that the atleast one distortion value associated with the system 100 a falls withina first threshold (e.g., a recalibration threshold) permitting use of afine unit of accuracy in dimensioning, volume, and cost determination.In the example depicted in FIG. 4A, the fine unit of accuracy is 1 mm.The volume dimensioning system 100 a is therefore able to determine thedimensions of the object 402 a to the nearest millimeter. Thus, thevolume dimensioning system 100 a is able to determine the length 406 aas 11.1 cm, the width 408 a as 6.3 cm, and the height 410 a as 15.6 cm.Using these determined dimensions, the volume dimensioning system 100 ais further able to determine the volume 412 a as 1091 cm³. Finally,using the determined volume and assuming a shipping cost of $0.015/cm³,the volume dimensioning system 100 a can calculate the shipping cost 414a for object 402 a is $16.37.

Object 402 b has dimensions identical to object 402 a, 11.1 cm inlength, 6.3 cm in width, and 15.6 cm in height. However, prior toplacement of the object 402 b in the field of view 210 of the imagingsensor 124, the volume dimensioning system 100 b has determined throughthe use of a reference pattern 202 (not shown in FIG. 4B) that the atleast one distortion value associated with the system 100 b fallsoutside a first threshold (e.g., a recalibration threshold) and within asecond threshold (e.g., a service required threshold) which permits theuse of a coarse unit of accuracy in dimensioning, volume determinationand cost determination. In the example depicted in FIG. 4B, the coarseunit of accuracy is 1 cm, an order of magnitude larger than the fineunit of accuracy used in FIG. 4A. The volume dimensioning system 100 bis therefore only able to determine the dimensions of the object 402 bto the nearest centimeter. Thus, the volume dimensioning system 100 bdetermines the length 406 b as 11 cm, the width 408 b as 6 cm, and theheight 410 b as 16 cm. Using these determined dimensions, the volumedimensioning system 100 b is further able to determine the volume 412 bas 1056 cm³. Finally, using the determined volume and assuming ashipping cost of $0.015/cm³, the volume dimensioning system 100 b isable to calculate the shipping cost 414 b for the object 402 b is$15.84.

In at least some instances, the volume dimensioning system 100 cancorrect distortion present in only a portion of the overall image. Forexample, the volume dimensioning system 100 may correct only the portionof the image containing the object 402. Such local correction canproceed using one or more correction factors determined based at leastin part on any distortion present in the portion of the image containingand/or proximate the object 402. Such local distortion correctionfactors can be used in a manner similar to image wide distortioncorrection factors, for example to determine the dimensional accuracyachievable with regard to the object 402 and to determine whether a fineunit of accuracy or a coarse unit of accuracy should be used inassessing dimensional and cost information for the object 402.

FIG. 5 is a flow diagram 500 showing a high level method of operation ofa volume dimensioning system 100. The method starts at 502. At 504 theat least one processor 126 receives pattern image data from the sensorsubsystem 118. In at least some instances, such pattern image data maybe autonomously acquired at regular or irregular intervals by the volumedimensioning system 100. For example, pattern image data may be acquiredat regular or irregular intervals when the all or a portion of thevolume dimensioning system 100 is received by the support member 302. Inother instances, such pattern image data may be manually acquired atregular or irregular intervals by the volume dimensioning system 100.For example, the volume dimensioning system 100 may provide one or morehuman perceptible indicators to a user that indicate the referencepattern 202 should be placed in the field of view of the at least onesensor 124 to permit the acquisition of pattern image data fordistortion correction or calibration purposes.

At 506 the at least one processor 126 determines at least one distortionvalue using the pattern image data received from the sensor subsystem118 at 504. The at least one processor 126 can determine any number ofdistortion values, including at least one of: an optical distortionvalue, a dimensional distortion value, a chromatic aberration ordistortion value, or combinations thereof. The distortion values sodetermined provide a quantitative measure or assessment of the overallquality of the image data provided by the sensor subsystem 118. In someinstances, all or a portion of the at least one distortion valuesdetermined by the at least one processor 126 at 506 can be stored orotherwise retained within the at least one non-transitory storage media130.

At 508 the at least one processor 126 compares the determined at leastone distortion value from 506 with a first distortion threshold. Adetermined at least one distortion value falling within the firstdistortion threshold indicates the distortion present in the image dataprovided by the sensor subsystem 118 is sufficiently small that a fineunit of accuracy may be used in determining and calculating dimensional,volumetric, and cost information. Conversely, a determined at least onedistortion value exceeding the first distortion threshold may indicatethe level of distortion present in the image data provided by the sensorsubsystem 118 is sufficiently large that the use of the fine unit ofaccuracy is inappropriate and a coarse unit of accuracy should insteadbe used to determine and calculate dimensional, volumetric, and costinformation. Such distortion thresholds may be provided as one or morefactory settings or one or more periodically updated thresholds that arestored or otherwise retained in the at least one non-transitory storagemedia 130.

Advantageously, such adjustments are made autonomously by the volumedimensioning system 100 without user intervention using the determinedat least one distortion value and a plurality of distortion thresholdsstored or otherwise retained within the non-transitory storage media130. For illustrative purposes, Table 1 lists one set of example valuesthat may be associated with “fine” and “coarse” units of accuracy:

TABLE 1 Example Units of Accuracy “Fine” Unit “Coarse” Unit of Accuracyof Accuracy Dimensional Units ½ inch 2 inches Volumetric Units 1 in³ 8in³ Cost Units $0.01 $0.10

At 510, if the at least one processor 126 finds the distortion valuedetermined at 506 is within or less than the first distortion threshold,the at least one processor 126 can adjust one or more volumedimensioning system parameters at 512. In at least some instances, at512 the one or more processors 126 may calculate one or more sets ofdistortion correction factors to reduce or eliminate the distortionpresent in the image data provided by the sensor subsystem 118 using theone or more distortion values determined at 506. In some instances,adjusting the one or more volume dimensioning system parameters at 512may also include confirming the fine units of accuracy are being used,performing one or more calibration routines, or combinations thereof.

At 514 the at least one processor compares the at least one distortionvalue determined at 506 with a second distortion threshold. If at 510the at least one processor 126 found the at least one distortion valuedetermined at 506 exceeded the first distortion threshold at 510, the atleast one processor 126 can compare the determined at least onedistortion value with a second distortion threshold at 514. In at leastsome instances, distortion values exceeding the second distortionthreshold may indicate the presence of distortion in the image dataprovided by the sensor subsystem 118 that is of a magnitude or severitysufficient to render the system 100 unusable based on one or morecorporate, industry, or regulatory guidelines, best practices, orstandards.

Although FIG. 5 illustrates the use of only two distortion thresholds,any number of distortion thresholds may be similarly used. Differentdistortion threshold values may be indicative, for example, of varyinglevels or degrees of distortion in the image data provided by the sensorsubsystem 118. Each of the different levels or degrees of distortion mayindicate the need for the system 100 to use a corresponding unit ofaccuracy in displaying dimensional, volumetric or cost information. Forexample a first threshold value may be indicative of distortion thatallows a unit of accuracy of 1 mm; a second threshold value may beindicative of distortion that allows a unit of accuracy of 2 mm; a thirdthreshold value may be indicative of distortion that allows a unit ofaccuracy of 3 mm; a fourth threshold value may be indicative ofdistortion that allows a unit of accuracy of 4 mm; a fifth thresholdvalue may be indicative of distortion that allows a unit of accuracy of5 mm; and a sixth threshold value may be indicative of distortionsufficient to generate a human perceptible “service required” indicatoron the system 100.

If at 516 the at least one processor 126 finds the at least onedistortion value determined at 506 exceeds or is greater than the seconddistortion threshold, the at least one processor 126 can generate one ormore human perceptible outputs indicative of a “service required”condition at 518. In some instances at 518, one or more functions orfeatures of the volume dimensioning system 100, for example the costingfunctionality, may be inhibited if the distortion value exceeds thesecond distortion threshold.

At 520, if the at least one processor 126 found the distortion valuedetermined at 506 fell between the first and the second distortionthresholds at 516, the at least one processor 126 can adjust the unitsof accuracy of the information presented by the volume dimensioningsystem 100. In at least some instances, at least one processor 126 canadjust dimensional, volumetric or cost information provided by thevolume dimensioning system 100 to one or more coarse units of accuracy.In at least some instances, at 520 the one or more processors 126 maycalculate one or more sets of distortion correction factors to reduce oreliminate the distortion present in the image data provided by thesensor subsystem 118 using the one or more distortion values determinedat 506. The one or more coarse units of accuracy cause the system 100 todetermine, calculate, and display dimensional, volumetric, and cost datain units of accuracy that are based at least in part on the capabilityof the system 100 to resolve such dimensions and volumes based on thedistortion values determined at 506. In at least some instances, some orall of the units of accuracy may be based on one or more corporate,industry, or regulatory guidelines, best practices, or standards. Insome instances, for example, the units of accuracy used by the volumedimensioning system may be based on the NIST Handbook 44-2012 Chapter5.58. The method 500 terminates at 522.

FIG. 6 is a flow diagram 600 showing a low level method of operation ofa volume dimensioning system 100. In particular, the method 600illustrates an example method that may be used by the at least oneprocessor 126 to assess the at least one distortion value at 506. Themethod 600 starts at 602. At 604 the at least one processor 126, usingthe pattern image data provided by the sensor subsystem 118, assessesthe optical distortion present in the image data by determining at leastone optical distortion value. The at least one optical distortion valuedetermined at 604 can provide a quantitative measure of the degree ormagnitude of the optical distortion present in the image data providedby the sensor subsystem 118. Such a quantitative measure of the opticaldistortion present in the image data may be obtained by the at least oneprocessor 126 using one or more numerical distortion analysistechniques, graphical distortion analysis techniques, or combinationsthereof.

At 606 the at least one processor 126 assesses the image data suppliedby the sensor subsystem 118 for dimensional distortion. The assessmentof the dimensional distortion by the at least one processor 126determines at least in part at least one dimensional distortion value.The at least one dimensional distortion value determined at 606 canprovide a quantitative measure of the degree or magnitude of thedimensional distortion present in the image data provided by the sensorsubsystem 118. Such a quantitative measure of the dimensional distortionpresent in the image data may be obtained by the at least one processor126 using one or more numerical distortion analysis techniques,graphical distortion analysis techniques, or combinations thereof. Afterthe at least one processor 126 has determined at least one distortionvalue attributable to either or both optical and dimensional distortionpresent in the image data provided by the sensor subsystem 118, themethod 600 concludes at 608.

FIG. 7 is a flow diagram 700 showing a low level method of operation ofa volume dimensioning system 100. In particular, the method 700illustrates an example method that may be used by the at least oneprocessor 126 to store historical distortion data including determineddistortion values and distortion correction factors in thenon-transitory storage media 130. Such historical data provides avaluable resource in tracking the performance history of the volumedimensioning system 100 and in providing a tool for predicting thefuture performance of the system 100. In some instances, collection ofsuch historical data may assist in compliance with one or morecorporate, industry, or regulatory guidelines, best practices, orstandards. Advantageously, since the determination of distortion valuesand distortion correction factors may be performed autonomously by thevolume dimensioning system 100, the presence of such historical data inthe non-transitory storage media 130 provides the system user withassurance that such distortion detection and correction routines arebeing performed by the system 100. The example method to storehistorical distortion data begins at 702.

At 704, the at least one processor 126 can associate one or moreidentifiers with the at least one distortion value determined at 506 orthe one or more sets of distortion correction factors determined at 512or 520. Any type of logical identifier, including one or more sequentialor chronological identifiers, may be so associated with the at least onedistortion value. The association of one or more logical identifierswith the at least one distortion value or the one or more sets ofdistortion correction factors permits the retrieval and presentation ofsuch data in an organized and logical manner. Storage of such historicaldata may also assist in compliance with one or more corporate, industry,or regulatory guidelines, best practices, or standards.

At 704 the at least one processor 126 can associate one or more logicalidentifiers with all or a portion of the distortion values (i.e.,determined at 506) or all or a portion of the calculated sets ofdistortion correction factors (i.e., calculated at 512 or 520). In atleast some instances, the one or more logical indicators can include oneor more chronological indicators such as date and time of determinationof the at least one distortion value or calculation of the set ofdistortion correction factors by the at least one processor 126. In someinstances, the one or more logical indicators can include one or moreserialized indicators sequentially assigned by the at least oneprocessor 126 upon determining the at least one distortion values orcalculating the set of distortion correction factors. Any similarlogical indicators that provide the ability to retrieve, sort, organize,or display the associated distortion values or distortion correctionfactors in a logical manner may be so assigned by the at least oneprocessor 126.

At 706, the at least one distortion value or the set of distortioncorrection factors and the associated logical identifier are at leastpartially stored within a non-transitory storage media 130. In at leastsome instances, at least a portion of the non-transitory storage media130 can include one or more types of removable media, for example securedigital (SD) storage media, compact flash (CF) storage media, universalserial bus (USB) storage media, memory sticks, or the like. The use ofsuch removable storage media may advantageously permit the transfer ofdata such as the stored distortion values and distortion correctionfactors to one or more external computing devices equipped with acomparable removable storage media reader.

At 708, the stored distortion values or distortion correction factorsare displayed sorted or otherwise arranged or organized by theassociated identifier either on the internal display device 132 of thevolume dimensioning system 100 or an external display device wiredly orwirelessly accessed by the system 100 via the communications subsystem108.

At 710, the stored distortion values or distortion correction factorsare displayed sorted by the associated identifier either on the internaldisplay device 132 of the volume dimensioning system 100 or an externaldisplay device wiredly or wirelessly accessed by the system 100 via thecommunications subsystem 108. Additionally, one or more trend lines maybe fitted to the displayed data to provide an indication of the overallrate of degradation or change in distortion of the image data providedby the sensor subsystem 118. Such trend data may be useful in detectingsudden or unexpected changes in the overall level of image data qualityprovided by the sensor subsystem 118 and may advantageously provide anindication of the overall condition of the sensor subsystem 118.

At 712, the stored distortion values or distortion correction factorsare displayed sorted by the associated identifier either on the internaldisplay device 132 of the volume dimensioning system 100 or an externaldisplay device wiredly or wirelessly accessed by the system 100 via thecommunications subsystem 108. Additionally, through the use of one ormore trend lines or similar data analysis techniques, a performanceforecast is provided. Such performance forecasts may identify anexpected date or timeframe in which the image data provided by thesensor subsystem 118 will no longer fall within an acceptable distortionthreshold. Such data may advantageously indicate or predict an expecteddate at which the sensor subsystem 118 or the volume dimensioning system100 may require service or replacement. The method 700 terminates at 714

The above description of illustrated embodiments, including what isdescribed in the Abstract, is not intended to be exhaustive or to limitthe embodiments to the precise forms disclosed. Although specificembodiments of and examples are described herein for illustrativepurposes, various equivalent modifications can be made without departingfrom the spirit and scope of the disclosure, as will be recognized bythose skilled in the relevant art. The teachings provided herein of thevarious embodiments can be applied to other automated systems, notnecessarily the exemplary volume dimensioning system generally describedabove.

For instance, the foregoing detailed description has set forth variousembodiments of the devices and/or processes via the use of blockdiagrams, schematics, and examples. Insofar as such block diagrams,schematics, and examples contain one or more functions and/oroperations, it will be understood by those skilled in the art that eachfunction and/or operation within such block diagrams, flowcharts, orexamples can be implemented, individually and/or collectively, by a widerange of hardware, software, firmware, or virtually any combinationthereof. In one embodiment, the present subject matter may beimplemented via Application Specific Integrated Circuits (ASICs).However, those skilled in the art will recognize that the embodimentsdisclosed herein, in whole or in part, can be equivalently implementedin standard integrated circuits, as one or more computer programsexecuted by one or more computers (e.g., as one or more programs runningon one or more computer systems), as one or more programs executed by onone or more controllers (e.g., microcontrollers) as one or more programsexecuted by one or more processors (e.g., microprocessors), as firmware,or as virtually any combination thereof, and that designing thecircuitry and/or writing the code for the software and or firmware wouldbe well within the skill of one of ordinary skill in the art in light ofthe teachings of this disclosure.

When logic is implemented as software and stored in memory, logic orinformation can be stored on any computer-readable medium for use by orin connection with any processor-related system or method. In thecontext of this disclosure, a memory is a computer-readable medium thatis an electronic, magnetic, optical, or other physical device or meansthat contains or stores a computer and/or processor program. Logicand/or the information can be embodied in any computer-readable mediumfor use by or in connection with an instruction execution system,apparatus, or device, such as a computer-based system,processor-containing system, or other system that can fetch theinstructions from the instruction execution system, apparatus, or deviceand execute the instructions associated with logic and/or information.

In the context of this specification, a “computer-readable medium” canbe any element that can store the program associated with logic and/orinformation for use by or in connection with the instruction executionsystem, apparatus, and/or device. The computer-readable medium can be,for example, but is not limited to, an electronic, magnetic, optical,electromagnetic, infrared, or semiconductor system, apparatus or device.More specific examples (a non-exhaustive list) of the computer readablemedium would include the following: a portable computer diskette(magnetic, compact flash card, secure digital, or the like), a randomaccess memory (RAM), a read-only memory (ROM), an erasable programmableread-only memory (EPROM, EEPROM, or Flash memory), a portable compactdisc read-only memory (CDROM), digital tape, and other nontransitorymedia.

Many of the methods described herein can be performed with one or morevariations. For example, many of the methods may include additionalacts, omit some acts, and/or perform or execute acts in a differentorder than as illustrated or described.

The various embodiments described above can be combined to providefurther embodiments. All of the commonly assigned US patent applicationpublications, US patent applications, foreign patents, foreign patentapplications and non-patent publications referred to in thisspecification and/or listed in the Application Data Sheet, including butnot limited to U.S. provisional patent application Ser. No. 61/691,093,filed is incorporated herein by reference, in its entirety. Aspects ofthe embodiments can be modified, if necessary, to employ systems,circuits and concepts of the various patents, applications andpublications to provide yet further embodiments.

These and other changes can be made to the embodiments in light of theabove-detailed description. In general, in the following claims, theterms used should not be construed to limit the claims to the specificembodiments disclosed in the specification and the claims, but should beconstrued to include all possible embodiments along with the full scopeof equivalents to which such claims are entitled. Accordingly, theclaims are not limited by the disclosure.

1.-27. (canceled)
 28. A volume dimensioning system, comprising: at leastone image sensor that provides image data representative of a pluralityof images of a field of view of the at least one image sensor; and acontrol subsystem communicatively coupled to the at least one imagesensor to receive the image data therefrom, the control subsystemincluding at least one non-transitory storage medium and at least oneprocessor, wherein the at least one non-transitory storage medium isconfigured to store at least one of information or processor executableinstructions, wherein the at least one processor is configured to:determine at least one distortion value indicative of an amount ofdistortion in the plurality of images; assess the at least onedistortion value relative to a plurality of distortion threshold values;and adjust an output of volume dimensioning related informationcomprising dimensional information, volume information, and costinformation from a first unit of accuracy to a second unit of accuracyin a reporting of volume dimensioning related information based at leastin part on the assessment of the at least one distortion value relativeto the plurality of distortion threshold values and shipping cost for anobject.
 29. The volume dimensioning system according to claim 28,wherein the at least one processor is further configured to compare thedetermined at least one distortion value with a first distortionthreshold value from the plurality of distortion threshold values,wherein the first distortion threshold value corresponds to arecalibration threshold.
 30. The volume dimensioning system according toclaim 29, wherein the at least one processor is configured to calculateone or more sets of distortion correction factors to eliminatedistortion in the plurality of images when the at least one distortionvalue is within or less than the first distortion threshold value. 31.The volume dimensioning system according to claim 29, wherein the atleast one distortion value exceeding the first distortion thresholdvalue indicates that a distortion present in the image data isdetermined by the second unit of accuracy to calculate the dimensionalinformation, the volume information, and the cost information.
 32. Thevolume dimensioning system according to claim 29, wherein the at leastone processor is further configured to compare the determined at leastone distortion value with a second distortion threshold value from theplurality of distortion threshold values when the at least onedistortion value exceeds the first distortion threshold value, whereinthe second distortion threshold value corresponds to a service requiredthreshold.
 33. The volume dimensioning system according to claim 32,wherein the at least one processor is further configured to generate oneor more human perceptible outputs when the at least one distortion valueexceeds the second distortion threshold value.
 34. The volumedimensioning system according to claim 33, wherein the at least oneprocessor is further configured to inhibit the reporting of the shippingcost of the object when the at least one distortion value exceeds thesecond distortion threshold value
 35. The volume dimensioning systemaccording to claim 32, wherein the output of volume dimensioning relatedinformation is adjusted from the first unit of accuracy to the secondunit of accuracy when the at least one distortion value is less than thesecond distortion threshold value.
 36. The volume dimensioning systemaccording to claim 28, wherein the first unit of accuracy corresponds toa fine unit of accuracy, wherein the second unit of accuracy correspondsto a coarse unit of accuracy.
 37. The volume dimensioning systemaccording to claim 28, wherein the at least one distortion valuecorresponds to an optical distortion value, a dimensional distortionvalue, a chromatic aberration or distortion value, or combinationthereof.
 38. The volume dimensioning system according to claim 28,wherein the plurality of distortion threshold values is provided as oneor more factory settings or one or more periodically updated thresholdvalues that are stored or retained in the at least one non-transitorystorage medium.
 39. The volume dimensioning system according to claim28, wherein the shipping cost for the object is based on a weightinformation of the object, volume information of the object, or both theweight information and the volume information of the object.
 40. Avolume dimensioning system, comprising: at least one image sensor thatprovides image data representative of a plurality of images of a fieldof view of the at least one image sensor; and a control subsystemcommunicatively coupled to the at least one image sensor to receive theimage data therefrom, the control subsystem including at least onenon-transitory storage medium and at least one processor, wherein the atleast one non-transitory storage medium is configured to store at leastone of information or processor executable instructions, wherein the atleast one processor is configured to: determine at least one distortionvalue indicative of an amount of distortion in the plurality of imagesbased at least in part on at least a portion of a decodable indiciawhich appears in the field of view of the at least one image sensor inat least some of the plurality of images; assess the at least onedistortion value relative to a plurality of distortion threshold values;and adjust an output of volume dimensioning related informationcomprising dimensional information and volume information from a firstunit of accuracy to a second unit of accuracy in a reporting of volumedimensioning related information based at least in part on theassessment of the at least one distortion value relative to theplurality of distortion threshold values.
 41. The volume dimensioningsystem according to claim 40, wherein the decodable indicia encodesinformation related to recipient information, sender information, andspecific handling instructions corresponding to an object.
 42. Thevolume dimensioning system according to claim 40, wherein physicalparameters associated with the decodable indicia are provided as one ormore factory settings or communicated to the at least one non-transitorystorage medium.
 43. The volume dimensioning system according to claim40, wherein the decodable indicia is mounted on a vertical surface. 44.A volume dimensioning method, comprising: receiving, by at least onedimensioning system processor, image data representative of a pluralityof images in a field of view of at least one image sensor; determining,by the at least one dimensioning system processor, at least onedistortion value indicative of an amount of distortion in the pluralityof images based at least in part on at least a portion of a calibrationpattern which appears in a field of view of the at least one imagesensor in at least some of the plurality of images, the calibrationpattern having a set of defined characteristics; assessing, by the atleast one dimensioning system processor, the at least one distortionvalue relative to a plurality of distortion threshold values stored in anon-transitory storage medium communicably coupled to the at least onedimensioning system processor; and adjusting, by the at least onedimensioning system processor, an output of reported volume dimensioningrelated information comprising dimensional information and volumeinformation from a first unit of accuracy to a second unit of accuracyin a representation of volume dimensioning related information based atleast in part on the assessment of the at least one distortion valuerelative to the plurality of distortion threshold values.
 45. The volumedimensioning method according to claim 44, further comprising storing,by the at least one dimensioning system processor, historical distortiondata including the at least one distortion value and one or moredistortion correction factors in the non-transitory storage medium. 46.The volume dimensioning method according to claim 45, furthercomprising: associating, by the at least one dimensioning systemprocessor, one or more logical identifiers with one or more distortionvalues that include the at least one distortion value and the one ormore distortion correction factors for an organized and logical dataretrieval and presentation; displaying, by the at least one dimensioningsystem processor, the one or more distortion values and the one or moredistortion correction factors in a sorted manner based on the associatedone or more logical identifiers, wherein the one or more distortionvalues and the one or more distortion correction factors are displayedin the sorted manner on an internal display device of a correspondingvolume dimensioning system or an external display device, wherein theexternal display device is accessed by the corresponding volumedimensioning system via a communications subsystem; and fitting, by theat least one dimensioning system processor, one or more trend lines tothe displayed one or more distortion values and the one or moredistortion correction factors to provide an indication of overall rateof change in distortion of the image data.
 47. The volume dimensioningmethod according to claim 44, further comprising performing, by the atleast one dimensioning system processor, one or more of tracking ofperformance history of a corresponding volume dimensioning system,predicting future performance of the corresponding volume dimensioningsystem, and assisting in compliance with one or more of standardguidelines and best practices.